The overall objective of this project is to reduce health disparities related to congenital hearing loss. The goal is to identify factors on which stae Early Hearing Detection and Intervention (EHDI) programs can intervene to increase follow-up evaluation rates for newborns that screen positive for hearing loss. Raising follow-up rates is needed to reduce disparities between children who are and are not born with hearing loss and between racial/ethnic minority and lower socioeconomic-status (SES) children, on the one hand, and white non-Hispanic and higher SES children, on the other. The Specific Aims of this study are to estimate the effects (risk ratios) of selected factors on 1) receiving a follow-up evaluatio vs. not receiving one; and 2) receiving a timely evaluation vs. a late one. Using eight years of birth, newborn hearing screening, and follow-up evaluation data from New Jersey, the analysis will incorporate hospital-level as well as child-level data. The approach taken in this study is ne in that 1) a data set that combines the four different types of data listed below will be created fr the analysis, 2) multilevel models will be used to estimate the risk ratios, and 3) the child will e the unit of analysis. Factors were selected for inclusion in the model if 1) there was evidence that the factor is associated with newborn hearing screening follow-up rates; 2) the factor can be intervened on by state EHDI programs; and 3) the factor had not previously been intervened on. The selected factors are as follows: 1. Two hospital factors-whether the birth hospital offers rescreening, and whether it has an audiology dept.; 2. Two characteristics of the hearing screen-screening method (OAE vs. ABR), and laterality of hearing loss; 3. Two aspects of medical condition-neonatal intensive care unit (NICU) stay, and cesarean delivery; 4. Two transportation factors-driving distance/time from residence to follow-up facility and availability f public transportation for that route, derived from the data using geographic information systems (GIS); and 5. Language combined with immigrant status. Furthermore, the models will include terms for interaction (effect modification) of the selected factors with race/ethnicity and SES in order to identify factors on which EHDI programs can intervene to reduce disparities by SES and race/ethnicity. Year of birth will be included in the models to allow for changes over time. If the Specific Aims of the proposed study are achieved, factors to target in the next generation of interventions that are aimed at increasing follow-up evaluation rates and reducing disparities will have been identified.